Evaluating the ability of the NLHA2 and artificial neural network models to predict COVID-19 severity, and comparing them with the four existing scoring systems.

To improve the identification and subsequent intervention of COVID-19 patients at risk for ICU admission, we constructed COVID-19 severity prediction models using logistic regression and artificial neural network (ANN) analysis and compared them with the four existing scoring systems (PSI, CURB-65, SMARTCOP, and MuLBSTA). In this prospective multi-center study, 296 patients with COVID-19 pneumonia were enrolled and split into the General-Ward-Care group (N = 238) and the ICU-Admission group (N = 58). The PSI model (AUC = 0.861) had the best results among the existing four scoring systems, followed by SMARTCOP (AUC = 0.770), motified-MuLBSTA (AUC = 0.761), and CURB-65 (AUC = 0.712). Data from 197 patients (training set) were analyzed for modeling. The beta coefficients from logistic regression were used to develop a severity prediction model and risk score calculator. The final model (NLHA2) included five covariates (consumes alcohol, neutrophil count, lymphocyte count, hemoglobin, and AKP). The NLHA2 model (training: AUC = 0.959; testing: AUC = 0.857) had similar results to the PSI model, but with fewer variable items. ANN analysis was used to build another complex model, which had higher accuracy (training: AUC = 1.000; testing: AUC = 0.907). Discrimination and calibration were further verified through bootstrapping (2000 replicates), Hosmer-Lemeshow goodness of fit testing, and Brier score calculation. In conclusion, the PSI model is the best existing system for predicting ICU admission among COVID-19 patients, while two newly-designed models (NLHA2 and ANN) performed better than PSI, and will provide a new approach for the development of prognostic evaluation system in a novel respiratory viral epidemic.

Erratum to hydrogen/oxygen mixed gas inhalation improves disease severity and dyspnea in patients with Coronavirus disease 2019 in a recent multicenter, open-label clinical trial.

[This corrects the article DOI: 10.21037/jtd-2020-057.].

Clinical course of COVID-19 in patients with pre-existing decompensated cirrhosis: initial report from China.

BACKGROUND: The clinical characteristics and disease course in COVID-19 patients with pre-existing decompensated cirrhosis has not been described so far. METHODS: In this case series, we report three patients with confirmed COVID-19 and pre-existing decompensated cirrhosis from three hospitals in Hubei, the epicenter of the outbreak in China. RESULT: Patient 1 was a 53-year-old man with hepatitis B virus-related cirrhosis, portal hypertension, and ascites. Though receiving intensive support, he died of irreversible multiple organ dysfunction syndrome 48 days after the onset of the illness. Patient 2 was a 75-year-old woman with a history of schistosomiasis-related cirrhosis, portal hypertension, and ascites. Her family members requested that invasive rescue measures not be undertaken, and she died of acute respiratory distress syndrome 40 days after presenting with COVID-19 infection. Patient 3 was an 87-year-old man with alcohol-related cirrhosis, portal hypertension, and esophageal variceal hemorrhage. He was discharged from the hospital 29 days after illness onset. CONCLUSION: The case series raise the possibility that decompensated cirrhosis may be a risk factor for a poor outcome in patients with COVID-19.